arXiv subjects

Sherif M. Abuelenin

Publications and source records attributed to Sherif M. Abuelenin.

13 recordsLinked to original sources

arXiv2023

Connectivity Analysis of Directed Highway VANETs using Graph Theory

Graph theory is a promising approach in handling the problem of estimating the connectivity probability of vehicular ad-hoc networks (VANETs). With a communication network represented as graph, graph connectivity indicators become valid for connectivity analysis of communication networks as well. In this article, we discuss two different graph-based methods for VANETs connectivity analysis showing that they capture the same behavior as estimated using probabilistic models. The study is, then, extended to include the case of directed VANETs, resulting from the utilization of different communication ranges by different vehicles. Overall, the graph-based methods prove a robust performance, as they can be simply diversified into scenarios that are too complex to acquire a rigid probabilistic model for them.

cs.NI↗

arXiv2022

Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation

As the Internet of Things (IoT) technology is being deployed, the demand for radio spectrum is increasing. Cognitive radio (CR) is one of the most promising solutions to allow opportunistic spectrum access for IoT secondary users through utilizing spectrum holes resulting from the underutilization of frequency spectrum. A CR needs to frequently sense the spectrum to avoid interference with primary users (PUs). Compressive spectrum sensing techniques have been gaining increasing interest in wideband spectrum sensing, as they reduce the need for high-rate analog-to-digital converters, reducing the complexity and energy requirements of the CR. In order to enhance spectrum sensing performance, researchers proposed to incorporate PU spectrum usage information into the process of spectrum sensing. Spectrum usage information can be obtained through pilot signals, geo-locational databases or through evaluation of previous spectrum sensing results. In this paper, we are studying the effects of compressive sensing parameters namely compression ratio, sensing period, and sensing duration on the estimation of primary user behavior statistics. We achieved an accurate estimation of the primary user's behavior while saving 40% of the sampling rate by using compressive spectrum sensing compared to traditional spectrum sensing with Nyquist rate sampling.

eess.SP↗

arXiv2020

Fading Improves Connectivity in Vehicular Ad-hoc Networks

Connectivity analysis is a crucial metric for network performance in vehicular ad-hoc networks (VANETs). Although VANET connectivity has been intensively studied and investigated under no-fading channel models for their simplicity, these models do not represent real-world scenarios that suffer channel impairments. The connectivity probability in a multipath propagation environment is too challenging to be caught by a closed formula due to the emerging complexity associated with the randomness in a fading channel. This leads to contradicting statements about the impact of fading on VANET connectivity. In this paper, we numerically estimate the connectivity probability using graph-based Monte-Carlo simulations aiming for better understanding of the connectivity in fading channels. The results show that Rayleigh-fading channels reinforce the connectivity compared to no-fading models at the same level of transmitting power and vehicle densities. While these findings may seem counterintuitive, they agree with similar behavior that was reported earlier in other ad-hoc networks. Using simulations and stochastic analysis, we thoroughly investigate this effect and provide an intuitive interpretation of the positive impact of fading on connectivity.

cs.NI↗

arXiv2018

On the similarity between Nakagami-m Fading distribution and the Gaussian ensembles of random matrix theory

We report the similarity between the Nakagami-m fading distribution and the three Gaussian ensembles of random matrix theory. We provide a brief review of random matrix theory and wireless fading. We show that the Nakagami-m distribution serves as mapping between the three ensembles. The statistics of the wireless fading amplitude, as modeled by Nakagami-m distribution, provide a rare example of a classically chaotic system that exhibits a transition between the Gaussian orthogonal, Gaussian unitary, and Gaussian symplectic ensembles of random matrix theory.

cs.IT↗

arXiv2018

Optimization of Dielectric Rod Antenna Design in Millimeter Wave Band for Wireless Communications

Dielectric rod antennas are promising candidates to be used in millimeter wave band wireless communications. The optimization of a patch-fed dielectric rod antenna design at millimeter wave band is presented in this work. This design is composed of simple dielectric rod antenna made of low cost Teflon with relative permittivity of 2.1 that is fed by a rectangular patch antenna. Compared to the conventionally used tapered dielectric rod antennas, this configuration is capable of producing higher gain for a given antenna length. The design is optimized to achieve gain up to 17.5 dBi and impedance bandwidth up to 4.4 GHz at 60 GHz. A 4-element array is proposed to increase the gain up to 21 dBi. Simulations are performed using CST microwave studio, and their results are presented.

physics.app-ph↗

arXiv2018

Closed-Form Mathematical Representations of Interval Type-2 Fuzzy Logic Systems

Interval type-2 fuzzy logic systems (IT2 FLSs) have a wide range of applications due to their abilities to handle uncertainties compared to their type-1 counterparts. This paper discusses the representation of IT2 FLSs in closed mathematical form. Two novel inference mechanisms are introduced, each of them represents a whole IT2 FLS. The two forms are based on approximating Coupland and John's geometric method and the Nie-Tan method. Having closed-form representations is preferred in the design of control systems, especially when stability analysis is studied. Additionally, the simplicity of the proposed mechanisms, offers an easy way for implementation. Simulation results show that the proposed method perform very closely to other methods. Simulation results are provided.

eess.SY↗

arXiv2018

On the spectral unfolding of chaotic and mixed systems

Random matrix theory (RMT) provides a framework to study the spectral fluctuations in physical systems. RMT is capable of making predictions for the fluctuations only after the removal of the secular properties of the spectrum. Spectral unfolding procedure is used to separate the local level fluctuations from overall energy dependence of the level separation. The unfolding procedure is not unique. Several studies showed that statistics of long-term correlation in the spectrum are very sensitive to the choice of the unfolding function in polynomial unfolding. This can give misleading results regarding the chaoticity of quantum systems. In this letter, we consider the spectra of ordered eigenvalues of large random matrices. We show that the main cause behind the reported sensitivity to the unfolding polynomial degree is the inclusion of specific extreme eigenvalue(s) in the unfolding process.

cond-mat.stat-mech↗

arXiv2017

Moment analysis of highway-traffic clearance distribution

To help with the planning of inter-vehicular communication networks, an accurate understanding of traffic behavior and traffic phase transition is required. We calculate inter-vehicle spacings from empirical data collected in a multi-lane highway in California, USA. We calculate the correlation coefficients for spacings between vehicles in individual lanes to show that the flows are independent. We determine the first four moments for individual lanes at regular time intervals, namely the mean, variance, skewness and kurtosis. We follow the evolution of these moments as the traffic condition changes from the low-density free flow to high-density congestion. We find that the higher moments of inter-vehicle spacings have a well defined dependence on the mean value. The variance of the spacing distribution monotonously increases with the mean vehicle spacing. In contrast, our analysis suggests that the skewness and kurtosis provide one of the most sensitive probes towards the search for the critical points. We find two significant results. First, the kurtosis calculated in different time intervals for different lanes varies smoothly with the skewness. They share the same behavior with the skewness and kurtosis calculated for probability density functions that depend on a single parameter. Second, the skewness and kurtosis as functions of the mean intervehicle spacing show sharp peaks at critical densities expected for transitions between different traffic phases. The data show a considerable scatter near the peak positions, which suggests that the critical behavior may depend on other parameters in addition to the traffic density.

physics.soc-ph↗

arXiv2016

Memristor model based on fuzzy window function

Memristor (memory-resistor) is the fourth passive circuit element. We introduce a memristor model based on a fuzzy logic window function. Fuzzy models are flexible, which enables the capture of the pinched hysteresis behavior of the memristor. The introduced fuzzy model avoids common problems associated with window-function based memristor models, such as the terminal state problem, and the symmetry issues. The model captures the memristor behavior with a simple rule-base which gives an insight of how memristors work. Because of the flexibility offered by the fuzzy system, shape and distribution of input and output membership functions can be tuned to capture the behavior of various real memristors.

cs.ET↗

arXiv2015

Empirical Study of Traffic Velocity Distribution and its Effect on VANETs Connectivity

In this article we use real traffic data to confirm that vehicle velocities follow Gaussian distribution in steady state traffic regimes (free-flow, and congestion). We also show that in the transition between free-flow and congestion, the velocity distribution is better modeled by generalized extreme value distribution (GEV). We study the effect of the different models on estimating the probability distribution of connectivity duration between vehicles in vehicular ad-hoc networks.

cs.NI↗

arXiv2015

Design and simulation of a hybrid controller for a multi-input multi-output magnetic suspension system

In this paper we present a Fuzzy Logic control approach designed to stabilize a multi-input multi-output magnetic suspension system. The system has four cubic floaters and four actuators that apply magnetic forces on the floaters, the suspension is performed by changing the voltages applied on the actuators, hence changing their currents, producing vertical magnetic forces that balance with the gravitational force. A fuzzy logic controller is used to control each actuator; the system is nonlinear and sensitive to initial conditions. Another fuzzy logic controller is used as a supervisory controller in order to increase the dynamic range of the system, enabling it to stabilize the floaters when the initial displacements are relatively big. Another design consideration was to keep the four floaters in the same plane as much as possible, to perform that task, a PD controller was set to modulate the currents of the four actuators in order to minimize an error signal measuring the relative vertical displacement of all the four floaters. Simulation results show that the designed control scheme stabilized the system for the design constrains.

eess.SY↗

arXiv2014

Decomposed Interval Type-2 Fuzzy Systems with Application to Inverted Pendulum

This article introduces the idea of decomposition of interval Type-2 fuzzy logic system into two parallel type-1 fuzzy systems. This decomposition avoids the problems associated with type-reduction techniques normally needed in type-2 fuzzy systems. Next, we compare the performance of a decomposed type-2 controller to the performance of a type-1 controller in stabilizing an inverted pendulum.

eess.SY↗

arXiv2013

Effect of Unfolding on the Spectral Statistics of Adjacency Matrices of Complex Networks

Random matrix theory is finding an increasing number of applications in the context of information theory and communication systems, especially in studying the properties of complex networks. Such properties include short-term and long-term correlation. We study the spectral fluctuations of the adjacency of networks using random-matrix theory. We consider the influence of the spectral unfolding, which is a necessary procedure to remove the secular properties of the spectrum, on different spectral statistics. We find that, while the spacing distribution of the eigenvalues shows little sensitivity to the unfolding method used, the spectral rigidity has greater sensitivity to unfolding.

math-ph↗